(1) Field of the Invention
This invention relates to an inference method and a knowledge-based system, and more particularly relates to those which learn associative knowledge from experience and are suited to use the learned knowledge in new problem solving.
(2) Description of the Related Art
It is necessary to collect all pieces of the knowledge required for problem solving in order for a knowledge-based system to function effectively. Almost all of the existing knowledge-based system need the knowledge to be elicited and provided by domain expert. While solving a problem we human beings are capable of learning strategic knowledge which is useful to solve a new problem and thus acquiring new knowledge. We often experience that by making association to our past experience and we become able to derive a solution to a problem which we could not at first by near use of the knowledge we had before.
There is a long history of machine learning. Inductive learning from examples have been popular in the past. However, since human beings learn more effectively the more background knowledge they have it has become recognized that learning from scratch is unrealistic and the recent main stream is a deductive learning in which domain theory is given as general knowledge and how it is used is learned. This approach is called Explanation-Based Learning or Explanation-Based Generalization, as described, for example in "Explanation-Based Generalization: A unifying view" by T. M. Mitchell et al, in Machine Learning Vol. 1, No. 1, pp 47-80, 1986 published by Kluwer Academic Publishers in England. This is a method which reflects human beings' characteristics that they analyze why a given solution to a problem can be a solution to the problem and apply the results of the analysis to a new problem.
However, this method works well only if a new problem can be solved by applying the whole solution mechanism of the problem experienced in the past. In fact, many of the problems encountered in daily life are ones which we feel somewhat similar to those experienced in the past. Invention of a learning method that can cope with those situations is strongly desired.